Journal Article

·2018

A comparative analysis of speech signal processing algorithms for Parkinson’s disease classification and the use of the tunable Q-factor wavelet transform

C. Okan Sakar , Görkem Serbes YTU , Ayşegül Gündüz , Hünkar Can Tunç , Hatice Nizam Ozogur , Betül Erdoğdu Şakar , Melih Tütüncü , Tarkan Aydın , M. Erdem Isenkul , Hülya Apaydın

Applied Soft Computing

No open-access abstract is available for this article. Use the DOI link on the right to read the full text.

Keywords

Feature extraction Computer science Wavelet transform Mel-frequency cepstrum Speech recognition Feature (linguistics) Voice activity detection Artificial intelligence Speech processing Signal processing Pattern recognition (psychology) Statistical classification Context (archaeology) Cepstrum Wavelet Digital signal processing

Subject Areas

Voice and Speech Disorders ·Physiology ·Health Sciences
Speech and Audio Processing ·Signal Processing ·Physical Sciences
Speech Recognition and Synthesis ·Artificial Intelligence ·Physical Sciences

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